code: def get_random_linear(in_channels, out_channels):
      linear = torch.nn.Linear(in_channels, out_channels)
      if dist.is_initialized():
          # Broadcast this tensor to the world so that the generated random tensor
          # is in sync in all distributed processes. See T45688819 for more
          # information.
          comm.get().broadcast(linear.weight, 0)
          comm.get().broadcast(linear.bias, 0)
  
      return linear
  
imports: import multiprocessing
  import os
  import sys
  import tempfile
  import traceback
  import unittest
  import warnings
  from functools import wraps
  import crypten.communicator
  import crypten.debug
  import torch
  import torch.distributed
  from crypten.config import cfg
label_desc: Use image node_id 3 for calling a global function with example usage: get_random_linear(in_channels, out_channels) and returns: linear